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Efficient multi-task learning with adaptive temporal structure for progression prediction
In this paper, we propose a novel efficient multi-task learning formulation for the class of progression problems in which its state will continuously change over time. To use the shared knowledge information between multiple tasks to improve performance, existing multi-task learning methods mainly...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer London
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10171734/ https://www.ncbi.nlm.nih.gov/pubmed/37362567 http://dx.doi.org/10.1007/s00521-023-08461-9 |